“…Use of both energy use for Miscanthus harvest and satellite imagery were good methods to characterize spatial variability of commercial production fields. …”
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“…To achieve this, Landsat 4-5 Thematic Mapper (TM) and Landsat 9 Operational Land Imager (OLI) imagery were utilized. LULC classification was performed using a supervised satellite image classification system, and the predictions were carried out using the cellular automata-artificial neural network (CA-ANN) algorithm. …”
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“…During effortless, meditative awareness, the whole family of alpha rhythm is synchronized including (a) Occipital-parietal alpha with visual clarity, formless color, and the absence of visual imagery (b) Frontal eye-field alpha with relatively motionless eyes, and the absence of voluntary actions or plans to move the eyes in some direction, along with nonactive working memory, (c) Somatosensory alpha or Mu rhythm from the somatic motor-sensory cortex with the resultant stillness of the body including head, face, larynx, spine, hands and legs, (d) Mid-temporal auditory alpha with vocal quietness and internal verbal silence (Maunam) with a feeling of spontaneous silence and serenity, (e) Cingulate and precuneus alpha resulting in freedom from autobiographical memories and the sense of agency or ego. …”
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“…We calculated landscape characteristics from composited and classified August 2018 PlanetScope satellite imagery. Negative binomial generalized linear models guided by a priori hypothesized relationships explored the association between hypothesized interactions of landscape structure and the outcome. …”
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“…Our results demonstrate the potential to map individual cover crop species using Sentinel-2 imagery, which is critical for understanding the environmental outcomes of increasing crop diversity on farms.…”
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“…However, manual processing of imagery is extremely time and labor intensive. Because of the associated expense, many studies have started to employ machine‐learning tools, such as convolutional neural networks (CNNs). …”
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“…This study proposes a meticulously curated and annotated dataset, named as SPIKE-segm, taken from the publicly accessible SPIKE dataset, and an optimal instance segmentation approach named as WheatSpikeNet for segmenting and counting wheat spikes from field imagery. The proposed method is based on the well-known Cascade Mask RCNN architecture with model enhancements and hyperparameter tuning to provide state-of-the-art detection and segmentation performance. …”
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“…Brain imaging research studies increasingly use “de-facing” software to remove or replace facial imagery before public data sharing. Several works have studied the effects of de-facing software on brain imaging biomarkers by directly comparing automated measurements from unmodified vs de-faced images, but most research brain images are used in analyses of correlations with cognitive measurements or clinical statuses, and the effects of de-facing on these types of imaging-to-cognition correlations has not been measured. …”
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“…It is relatively easier to attain a 10-mrad level angular resolution with muon trackers that have been used for muographic imagery. Therefore, Vector muPS retains the unique capacity to operate wirelessly in indoor environments and also has the capacity to achieve a cm-level accuracy. …”
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“…While maintaining the common principles of geobotanical subdivision, we derived the boundary between the High and Low Arctic using the most up‐to‐date field data and modern techniques: species distribution modeling, radar, thermal and optical satellite imagery processing, and climatic data analysis. The position of the High–Low Arctic boundary in Western Siberia was clarified and mapped. …”
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“…Different indices characterizing the mesozooplankton are compared: biomass dry weight of four size fractions between 200 and 2000 μm; abundances of the whole of the mesozooplankton and of 13 main taxonomic groups defined from plankton imagery; seasonal onset timing of each zooplankton group; and two other types of indices: the first characterized diversity based on abundance data, and the second was derived from zooplankton size spectra shape. …”
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“…The neurocognitive mechanisms (e.g., visual search behavior, imagery), methodological aspects (e.g., adaptive training difficulty), and the issues of real-world transfer and generalizability via which these potential sports-performance-related improvements may occur are discussed. …”
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“…Using US Energy Information Administration (EIA) data, locations of 3,699 LSPV facilities were verified using high-resolution aerial imagery, polygons were digitized around panel arrays, and attributes were appended. …”
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“…Participants in the MT group received standard care and an MT intervention by a certified music therapist qualified in guided imagery and music. The CG patients received the standard of care. …”
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“…Variations occur mainly for blurred out-of-focus imagery exhibiting larger degrees of cell overlaps in clusters of erythrocytes. …”
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“…METHODOLOGY/PRINCIPAL FINDINGS: Using a combination of cell imagery and sucrose gradient fractionation, we show that HuR localization is highly dynamic during spermatid differentiation. …”
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“…We also present supplementary results including one healthy subject using motor imagery, one primary lateral sclerosis (PLS) patient, and one healthy subject using a single EEG channel without Laplacian derivation. …”
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“…To determine the distribution and density of the fly, tsetse surveys were conducted throughout the study area in the dry and in the rainy season. Landsat ETM+ imagery covering the study area were classified into four land cover classes (munga, miombo, agriculture and settlements) and two auxiliary spectral classes (clouds and shadow) using a Gaussian Maximum Likelihood Classifier. …”
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“…These results indicate a functional dissociation between higher order areas for observational learning (i.e. parts of the MNS as reflected in 10Hz coherence measures) and peripheral structures (i.e. lateral occipital gyrus for alpha; central sulcus for mu) that provide low-level support for observation and motor imagery of action sequences.…”
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“…INTRODUCTION: Historically, effective clinical utilization of image analysis and pattern recognition algorithms in pathology has been hampered by two critical limitations: 1) the availability of digital whole slide imagery data sets and 2) a relative domain knowledge deficit in terms of application of such algorithms, on the part of practicing pathologists. …”
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